In order to observe the morphology of a sample, such as a section of biological tissue, and simultaneously measure the distribution of the molecules existing in a specified area on the sample, a type of system called a mass microscope or an imaging mass spectrometer has been developed (for example, refer to Patent Documents 1-3 as well as Non-Patent Documents 1 and 2). These systems require no grinding or crushing of the sample and hence are capable of obtaining a distribution image (or mapping image) of the ions having a specific mass-to-charge ratio (m/z) included in any area specified on the sample based on a microscopic observation while almost completely maintaining the original morphology of the sample. Such systems are expected to be used, for example, to obtain distribution information of the proteins included in a living cell, particularly in the fields of biochemistry, medical care, pharmaceutical chemistry, and other applications.
It is important for an analysis operator to easily grasp desired information on a sample, such as the kind of substance that characterizes the sample or the distribution of the amount of that substance. To this end, an appropriate analysis processing should be performed on the collected mass spectrometric imaging data, and the result of the processing should be displayed in an appropriate form. If mass spectrometric imaging data are obtained for a two-dimensional area of a certain area on a sample, the data will include mass spectrum data of many measurement points (micro areas). Naturally, the amount of these data is enormous. Given this problem, various methods have been proposed to process such an enormous amount of data and extract significant information in an easy-to-understand fashion for the analysis operator.
In one method, for example, an integrated mass spectrum created by integrating the mass spectra of all measurement points is displayed on a display screen, on which the analysis operator can appropriately select a peak among the peaks appearing on the integrated mass spectrum. After selecting a peak, the analysis operator can display the intensity spatial distribution of that peak by using a commonly available mass-spectrum (MS) image display software product, such as BioMap (for example, refer to Non-Patent Document 3). Superimposing the spatial distributions of the intensity of two or more peaks in this manner provides information relating to the structure of a specified tissue and the mass-to-charge ratio of the main substance of the tissue.
Another type of method uses a multivariate analysis, such as a principal component analysis (PCA), independent component analysis (ICA) or factor analysis (FA) (for example, refer to Non-Patent Document 4). In the multivariate analysis, two or more substances forming close intensity spatial distributions gather by factors. Typically, a score and a loading are displayed in terms of each of the factors. In the method described in Non-Patent Document 4, the score is displayed as a two-dimensional spatial distribution, and the loading as a scatter diagram.
However, the previously described conventional methods have the following disadvantages: In an analysis method using MS image display software, when an analysis operator selects a peak on an integrated mass spectrum, the intensity spatial distribution for the mass-to-charge ratio corresponding to the selected peak is displayed. This method does not guarantee that the selected peak always corresponds to a substance that shows a spatially specific distribution. If a peak showing a spatially specific distribution must be located for each small area on a sample, the analysis operator needs to compare and superimpose the intensity spatial distributions of two or more peaks by trial and error. Consequently, the operator normally has to repeat the operation of displaying images for many peaks on the integrated mass spectrum, which requires a large amount of time and labor.
In the methods using a multivariate analysis, specialized knowledge and skills are required in many cases to determine the number of factors and interpret the loading value of each factor. In the case of PCA, a peak having a negative intensity may be included on the displayed mass spectrum of a main component and it is sometimes difficult to interpret the physical meaning of the result. Therefore, only a limited number of operators can conduct the analysis, which makes it difficult to efficiently perform the analysis and enhance the throughput. Another disadvantage of the PCA method exists in that the information obtained by this method is insufficient for determining the spatial distribution or content of a substance; the information relating to one substance is reflected in a plurality of main components, whereas the PCA method provides the spatial distribution of only one main component.